Application of Stochastic Subspace Identification in Bridge Health Monitoring, and Study on Effects of Temperature Fluctuations on Frequency Changes

Ambient vibration tests and real-time health monitoring have become more accepted in civil engineering. Time domain and frequency domain algorithms have been used in structural identification using the output-only measurements. The purpose of this paper was to investigate the effectiveness of the data-driven subspace identification algorithms in modal analysis of bridges from output-only measurements. The stochastic subspace identification (SSI) algorithm was examined through a numerical truss bridge and a real concrete highway bridge. In the modal identifications, the simulated dynamic responses of the truss bridge with abrupt damages during the excitation and the actual acceleration measurements from a real-time health monitoring system were used as the output data for the numerical truss bridge and the real highway bridge respectively. Stabilization diagrams with a range of model orders were used to determine the modal frequencies, damping ratios, and mode shapes. As one of the environmental conditions, temperature fluctuations can have a great effect on the dynamic characteristics of bridges. It is useful to learn the pattern of changes in frequencies due to temperature fluctuations. The variation of frequencies with respect to temperature was investigated using one-year ambient vibration data of a highway bridge. The modal frequencies and temperatures were correlated, which showed that such correlations for most modes can be represented by single or bilinear lines.

References
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